Construction and Validation of a Risk Assessment Model for Sepsis-Associated Acute Lung Injury in Patients with Sepsis in the Intensive Care Unit.

IF 2.7 3区医学 Q2 CRITICAL CARE MEDICINE

SHOCK Pub Date : 2025-04-01 DOI:10.1097/SHK.0000000000002591

Lulu Weng, Haidong Li, Jiawen Shi, Li Zhong

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引用次数: 0

Abstract

Purpose: Sepsis-Associated Acute Lung Injury (SALI) represents a severe complication in sepsis patients, leading to poor clinical outcomes and increased mortality. This study aimed to develop and validate a reliable nomogram for early prediction of SALI in adult critically ill patients, addressing the critical need for timely risk stratification and intervention.

Methods: A retrospective cohort study was conducted involving 345 intensive care unit (ICU) sepsis patients from the First People's Hospital of Huzhou. Patients were randomly divided into training (n = 241) and validation (n = 104) cohorts. Multivariate logistic regression and LASSO regression were employed to identify independent risk factors and construct a predictive nomogram.

Results: Four independent risk factors were identified: PaCO2, PaO2, serum uric acid (SUA), and SOFA score. The developed nomogram demonstrated excellent discriminative performance, with area under the receiver operating characteristic curve (AUC) of 0.916 in the training cohort and 0.931 in the validation cohort. Calibration curves, decision curve, and SHapley Additive exPlanations (SHAP) analysis confirmed the model's robust predictive performance and clinical utility.

Conclusions: The novel nomogram provides a practical, visualized risk assessment tool for early SALI recognition, potentially improving patient outcomes through enhanced understanding and timely interventions in critically ill patients.

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重症监护室脓毒症患者脓毒症相关急性肺损伤风险评估模型的构建与验证

目的：脓毒症相关急性肺损伤（SALI）是脓毒症患者的严重并发症，导致临床预后差和死亡率增加。本研究旨在开发和验证一种可靠的nomogram，用于早期预测成人危重患者SALI，解决及时进行风险分层和干预的迫切需求。方法：对湖州市第一人民医院重症监护病房（ICU）脓毒症患者345例进行回顾性队列研究。患者被随机分为训练组（n = 241）和验证组（n = 104）。采用多元逻辑回归和LASSO回归识别独立危险因素，构建预测模态图。结果：确定了4个独立危险因素：PaCO2、PaO2、血清尿酸（SUA）和SOFA评分。所建立的nomogram具有良好的判别性能，训练组和验证组的受试者工作特征曲线下面积（AUC）分别为0.916和0.931。校准曲线、决策曲线和SHapley加性解释（SHAP）分析证实了该模型的稳健预测性能和临床实用性。结论：这种新型的nomographic为早期SALI识别提供了一种实用的、可视化的风险评估工具，通过加强对危重患者的理解和及时干预，有可能改善患者的预后。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

SHOCK 医学-外科

CiteScore

6.20

自引率

3.20%

发文量

199

审稿时长

1 months

期刊介绍： SHOCK®: Injury, Inflammation, and Sepsis: Laboratory and Clinical Approaches includes studies of novel therapeutic approaches, such as immunomodulation, gene therapy, nutrition, and others. The mission of the Journal is to foster and promote multidisciplinary studies, both experimental and clinical in nature, that critically examine the etiology, mechanisms and novel therapeutics of shock-related pathophysiological conditions. Its purpose is to excel as a vehicle for timely publication in the areas of basic and clinical studies of shock, trauma, sepsis, inflammation, ischemia, and related pathobiological states, with particular emphasis on the biologic mechanisms that determine the response to such injury. Making such information available will ultimately facilitate improved care of the traumatized or septic individual.